Marius Lange (formerly Helmholtz Munich, now ETH Zurich), one of the study’s first authors, explains: “studying processes like development, disease, or regeneration has traditionally been challenging because analyzing cells over time usually requires destroying them to measure their internal states, breaking their natural cell lineage, or ‘family tree’. Current methods use gene activity snapshots to connect cells across different time points, but this approach misses out on the full picture. Moslin’s unique approach is the first to combine both family tree information and gene activity from multiple points in time, providing a clearer, more accurate picture of cell evolution.”
How Moslin Traces Cell Fate
Moslin works by creating a “map” that links related cells over time, allowing scientists to predict how cells might change in the future and what drives these changes. In testing, Moslin outperformed other methods by accurately predicting cell paths in simulated data. In real-world applications, such as studying the development of C. elegans worms and zebrafish heart healing, Moslin has helped researchers identify key gene signals that influence cell behavior.
Potential for Medical Advances
By combining information about gene activity and cell family trees, Moslin could improve our understanding of how cells make decisions. This knowledge may lead to breakthroughs in regenerative medicine, where knowing how to guide cells to grow into specific types is essential.
The Moslin software is freely available, complete with guides and tutorials, at github.com/theislab/moslin.
Original publication
Lange, Piran, Klein, Spanjaard et al. (2024): Mapping lineage-traced cells across time points with moslin. Genome Biology. DOI: 10.1186/s13059-024-03422-4
